This book provides an introduction to vector optimization with variable
ordering structures, i.e., to optimization problems with a vector-valued
objective function where the elements in the objective space are
compared based on a variable ordering structure: instead of a partial
ordering defined by a convex cone, we see a whole family of convex
cones, one attached to each element of the objective space. The book
starts by presenting several applications that have recently sparked new
interest in these optimization problems, and goes on to discuss
fundamentals and important results on a wide range of topics. The theory
developed includes various optimality notions, linear and nonlinear
scalarization functionals, optimality conditions of Fermat and Lagrange
type, existence and duality results. The book closes with a collection
of numerical approaches for solving these problems in practice.